Trends in Risk Perceptions and Vaccination Intentions: A Longitudinal Study of the First Year of the H1N1 Pandemic

Abstract

Objectives. We sought to evaluate longitudinal trends in people’s risk perceptions and vaccination intentions during the 2009 H1N1 pandemic.

Methods. We used data from 10 waves of a US national survey focusing on the H1N1 pandemic (administered between May 2009 and January 2010) to conduct a longitudinal analysis of adult respondents’ risk perceptions and vaccination intentions.

Results. Self-reported perceived risk of becoming infected with H1N1 paralleled H1N1 activity throughout the pandemic’s first year. However, intention to be vaccinated declined from 50% (May 2009) to 16% (January 2010) among those who remained unvaccinated (27% had been vaccinated by January 2010). Respondents who indicated that they had previously been vaccinated against seasonal influenza reported significantly higher H1N1 vaccination intentions than those who had not been vaccinated (67% vs 26%; P < .001).

Conclusions. Reported intention to be vaccinated declined well before vaccine became available and decreased throughout the pandemic year. To the extent that prior vaccination for seasonal influenza vaccination is a strong correlate of H1N1 risk perceptions, encouraging seasonal influenza vaccination may benefit pandemic preparedness efforts.

Vaccination is one of the most effective means of controlling illness caused by influenza. At no time is control more critical than when a new strain of influenza emerges, causing a pandemic. Willingness to be immunized against a novel strain of influenza appears to change over time,¹ yet little is known about how willingness changes with perceived risk as a pandemic evolves from an early threat of unknown severity to a more mature threat with known parameters. To be effective in limiting the spread of the disease, strategies to optimize vaccination rates during a pandemic must take into account the public’s changing perceptions of risk to target those who are hesitant to be vaccinated. Opportunities to gain an in-depth understanding of vaccination behaviors are hampered by the infrequency of pandemics and the lack of longitudinal data on risk perceptions.

The recent H1N1 pandemic offered an opportunity to study evolving vaccination behaviors. On March 28, 2009, a 9-year-old California girl became the first individual with a confirmed case of H1N1 influenza in the United States.² Within 1 month the United States declared a public health emergency,³ and within 2 months the World Health Organization declared a phase 6 pandemic (the highest level possible).⁴ Fortunately, by August 2009 it became clear that the death rate from H1N1 was only about 0.1% to 0.3%, comparable to that expected from seasonal influenza, according to a report by the President’s Council of Advisors on Science and Technology.⁵

However, there was ongoing concern that up to half of the population could become infected, with the number of deaths expected to range from 30 000 to 90 000. By September 2009, a vaccine for the novel H1N1 strain had been approved by the Food and Drug Administration.⁶ In anticipation of this development, the Advisory Committee on Immunization Practices released criteria for vaccine prioritization in late July 2009.⁷ Vaccination began in October 2009. Although production delays impeded initial distribution, more than 61 million vaccine doses were ready by November 2009.⁸

Despite the availability of a safe and effective H1N1 vaccine⁶ and an unprecedented public health campaign to promote its use, uptake by December 2009 was disappointingly low. Only 24% of the entire US population had been vaccinated, and the percentage was only somewhat higher (33%) for priority vaccination groups.⁹

The failure to achieve widespread vaccination uptake has many possible causes. We speculate that some of the failure reflects the public’s evolving perceptions of H1N1 risk. Previous research has highlighted subjective risk as a key predictor of vaccine uptake.¹⁰ Yet, almost nothing is known about how the public’s perceptions of novel risks such as H1N1 track the actual evolution of a pandemic or whether variations in risk perceptions explain subsequent patterns in vaccination intentions and behaviors. Previous studies have examined the relationship between risk perceptions and intentions at a single point in time,^11,12 but a longitudinal perspective is more policy relevant given that risk perception evolves over time.

We sought to chronicle the US public’s evolving risk perceptions regarding the 2009 H1N1 influenza pandemic and the relationship of these perceptions to vaccination intentions. We drew on the ability of RAND’s American Life Panel (ALP) to field frequent interviews with a common sample to generate a detailed, longitudinal perspective of risk perceptions and vaccination intentions throughout the 2009 H1N1 pandemic. Our research questions were as follows: How did perceived risk of H1N1 infection and of death given H1N1 infection relate to measured disease activity in the US population? Did perceived risk of H1N1 correlate with reported intention to be vaccinated against H1N1? and What other policy-relevant factors were associated with H1N1 vaccination intentions over time?

METHODS

We analyzed data from online surveys of US adults aged 18 to 91 years participating in the ALP. ALP panelists are recruited from respondents to the University of Michigan’s long-standing Survey of Consumer Attitudes. Panelists agree to respond to surveys regularly in exchange for financial compensation. The panel includes both online and offline populations (WebTV is supplied to participants who lack Internet access). (A detailed description of the ALP is available at http://www.rand.org/labor/roybalfd/american_life.html, and a comparison with the Current Population Survey is available at https://mmicdata.rand.org/alp/index.php/Main_Page.¹³)

The survey was fielded in 10 waves beginning on the following dates (with numbers of completed responses in parentheses):

1. May 26, 2009 (n = 2070),

2. June 8, 2009 (n = 1979),

3. June 22, 2009 (n = 1987),

4. July 6, 2009 (n = 1932),

5. July 20, 2009 (n = 1874),

6. August 3, 2009 (n = 2081),

7. August 17, 2009 (n = 1942),

8. September 22, 2009 (n = 2090),

9. November 19, 2009 (n = 2368), and

10. January 22, 2010 (n = 2504).

We included in our study only panel members who were eligible to participate in all 10 waves.

Survey Questions and Data

Every survey wave included 3 core questions. Intention to be vaccinated against H1N1 was measured by asking respondents to estimate the “chances” that they would get an H1N1 vaccine; participants indicated their estimate on a clickable, visual probability scale ranging from 0% to 100% (see Figure A, available as a supplement to the online version of this article at http://www.ajph.org). This response mode has been used successfully in past studies of intention^14,15 and other expectations,^16–18 and it has been shown to improve aggregate-level predictions of future actions relative to binary “yes–no” measures.^14,15

In the November 2009 and January 2010 waves, respondents who had already been vaccinated against H1N1 were not asked about their intention to be vaccinated, but their intention was coded as 100% once they reported vaccination. All respondents were asked to use the same 0% to 100% visual scale to estimate their risk of contracting H1N1 influenza over the next month as well as their risk of death conditional on contracting H1N1 influenza.

Other key questions asked about past receipt of influenza vaccine and risk factors that would place the respondent in a priority group for receipt of H1N1 vaccine.⁷ Demographic variables included age, gender, race, income, education, and state of residence, which was recoded as region of residence, corresponding to the 10 Department of Health and Human Services regions.¹⁹ Respondents used categories defined by the ALP and based on US Census classifications to self-classify their race and ethnicity.²⁰ Race and ethnicity data are collected when panelists enter the ALP and quarterly thereafter for the purposes of describing panelists’ demographic characteristics.

We used publicly available data from the Centers for Disease Control and Prevention (CDC) to construct an objective, longitudinal record of influenza activity against which to compare risk perceptions and intention to be vaccinated.²¹ Each week, the CDC reports information collected through the US Outpatient Influenza-like Illness Surveillance Network on percentage of outpatient visits to health care providers for influenza-like illness. This network comprises 3000 health care providers in all 50 states, the District of Columbia, and the US Virgin Islands reporting more than 25 million patient visits each year.²² We also used data from the CDC on laboratory-confirmed influenza hospitalizations starting in October 2009. Prior to October 2009, this information either was reported only by stratified age groups or was reported in combination with syndromic surveillance-based hospitalizations.

Analyses

We used the χ² test and Fisher’s t test to evaluate differences between responders and nonresponders. We conducted descriptive analyses and constructed 3 separate linear regression models with the following outcomes: perceived risk of contracting H1N1 influenza over the next month, perceived risk of death from H1N1 if infected, and intention to be vaccinated against H1N1. Covariates included demographic characteristics, membership in a priority group for H1N1 vaccine, receipt of seasonal influenza vaccine in the previous season, region of residence, and survey wave. Because of repeated measurements, we used robust standard errors to account for intrasubject clustering. Adjusted means for each covariate were generated from the multivariate models.

Our data on perceived risk of contracting and dying from H1N1 and vaccination intentions were bounded (between 0 and 100), yet linear regressions assume unbounded dependent variables. As a robustness check, we ran ordered logistic regression models that accounted for the bounded nature of the data but ignored the interval nature of participants’ responses. The results from these models were similar to those of the linear regression models. For parsimony, we report here only the linear regression models taking into account the full cardinal properties of the data.

RESULTS

The response rates for the waves, as defined by the number of complete surveys divided by the size of the selected sample for the wave in question, varied from 64% (wave 5) to 73% (wave 10). Over the 10 waves, there were 19 341 observations from 2530 unique respondents. There were no significant differences between respondents and nonrespondents in terms of age, income, or gender. However, respondents were significantly more likely to be White (89% vs 83%; P < .001) and to have a bachelor’s degree or higher (44% vs 37%; P < .001).

The mean age of the respondents was approximately 49 years (SD = 15 years), and 42% were male (see Table A, available as a supplement to the online version of this article at http://www.ajph.org). About 44% had a bachelor’s degree or higher, and 89% were White. Overall, 9% had been vaccinated for H1N1 by the end of November 2009 and 27% by the end of January 2010. Twenty-three percent were in an H1N1 high-priority group (per the guidelines of the Advisory Committee on Immunization Practices). Of the respondents in high-priority groups, 19% had been vaccinated for H1N1 by the end of November and 38% by the end of January. Almost half (44%) of the wave 1 respondents reported receiving a seasonal vaccine in the previous year.

Risk Perception and Vaccination Intention Patterns Over Time

Respondents reported a mean perceived risk of contracting H1N1 influenza in the next month of about 9% during the first wave, and this percentage slowly increased over the summer (Figure 1a). Perceived risk spiked to 18% from August to September and then declined over the next few months to 11% by the end of January. This curve largely paralleled objective influenza activity (percentage of outpatient visits made for influenza-like illness and hospitalizations).

FIGURE 1—

Patterns of H1N1 influenza activity, risk perceptions, and intention to be vaccinated over time: American Life Panel Survey Respondents, 2009–2010.

Note. ILI = influenza-like illness. For panel a only, visits are percentage of all outpatient visits; hospitalizations are in thousands.

Source. Centers for Disease Control and Prevention, Influenza Division, Epidemiology and Prevention Branch (panel a).

Respondents’ perceived risk of death if infected with H1N1 influenza was initially high at 14% and then fell, with a small spike to about 13% in July. It declined from the summer through January 2010 to about 10% (Figure 1b).

Intention to be vaccinated against H1N1 (Figure 1c) was highest at the beginning of the pandemic, at 50%, and steadily decreased over time. The lowest point was during the final wave of the survey, at 16% for respondents who remained unvaccinated. However, because some respondents had been vaccinated by January, the denominator for this curve decreased for the final 2 waves.

The upper branch in Figure 1c includes the 27% of the sample vaccinated by January (by imputing their intention to be 100% once they had been vaccinated), shifting the overall mean vaccination intention rate to 37%, which is still substantially lower than the mean stated intention at wave 1. To provide an alternate characterization of constant cohorts, Figure 1d stratifies participants’ responses in earlier waves according to whether they had received the H1N1 vaccine by the end of January. Mean intention to be vaccinated was uniformly higher among those who were ultimately vaccinated than among those who remained unvaccinated. However, the slope of the decline was similar in the 2 groups, as evidenced by the largely parallel curves.

Factors Predicting Risk Perceptions and Vaccination Intentions

Increased perceived risk of H1N1 infection within the next month (Table 1) was associated with female gender, lower income, non-White race, lower education, and receipt of seasonal influenza vaccine in the past season. In general, responses during later waves (from July 2009 onward) were associated with increased perceived risk; the exception was the January 2010 wave, which was associated with a lower coefficient than the 5 previous survey waves.

TABLE 1—

Results of Multivariate Linear Regression Model Predicting Perceived Risk of H1N1 Infection: American Life Panel Survey Respondents, 2009–2010

	Perceived Risk of H1N1 Infection (n = 17 501)
	b (95% CI)	Adjusted Mean, %
Gender
Male	−1.70 (−2.65, −0.74)	10.1
Female		12.2
Age, y	−0.01 (−0.05, 0.02)
25th percentile		11.5
75th percentile		11.2
Income, $
< 25 000	Ref	13.4
25 000–49 999	−0.28 (−2.13, 1.57)	12.9
50 000–74 999	−1.34 (−3.21, 0.53)	11.3
> 75 000	−2.74 (−4.48, −0.99)	9.3
Race
White	−6.37 (−8.59, −4.13)	10.7
Non-White		17.4
Bachelor’s degree or higher	−2.40 (−3.35, −1.44)
Yes		9.6
No		12.6
High-priority group	1.24 (0.00, 2.48)
Yes		13.0
No		10.8
Receipt of seasonal influenza vaccine in prior y	4.72 (3.69, 5.75)
Yes		13.5
No		9.6
Survey wave
1	Ref	9.4
2	−0.17 (−0.80, 0.46)	9.3
3	−0.31 (−0.93, 0.31)	9.1
4	−0.21 (−0.85, 0.42)	9.2
5	0.80 (0.04, 1.56)	10.2
6	1.35 (0.54, 2.17)	10.8
7	1.37 (0.66, 2.08)	10.8
8	7.96 (7.04, 8.89)	17.4
9	7.29 (6.43, 8.15)	16.7
10	0.77 (0.04, 1.50)	10.2

Note. CI = confidence interval. Analyses controlled for region of residence and for clustering by respondent.

Increased perceived risk of dying if infected with H1N1 (Table 2) was significantly associated with lower income, non-White race, lower education, and receipt of seasonal influenza vaccine in the previous year. Relative to May 2009, mean perceived risk of dying in each survey wave decreased slightly through January 2010 but remained far higher than the actual risk of death (0.1%–0.3%).

TABLE 2—

Results of Multivariate Linear Regression Models Predicting Perceived Risk of Dying From H1N1 if Infected: American Life Panel Survey Respondents, 2009–2010

	Perceived Risk of Death if Infected (n = 17 475)
	b (95% CI)	Adjusted Mean (%)
Gender
Male	−1.00 (−2.23, 0.23)	10.3
Female		12.0
Age, y	0.04 (−0.01, 0.09)
25th percentile		10.8
75th percentile		11.8
Income, $
< 25 000	Ref	17.4
25 000–49 999	−3.30 (−5.87, −0.73)	13.6
50 000–74 999	−5.71 (−8.25, −3.18)	10.5
> 75 000	−7.80 (−10.24, −5.37)	7.7
Race
White	−7.40 (−10.01, −4.80)	10.5
Non-White		18.6
Bachelor’s degree or higher	−3.52 (−4.74, −2.30)
Yes		8.4
No		13.6
High-priority group	1.48 (−0.03, 3.00)
Yes		13.0
No		10.8
Receipt of seasonal influenza vaccine in prior y	3.31 (2.04, 4.58)
Yes		12.8
No		10.1
Survey wave
1	Ref	13.7
2	−1.21 (−1.89, −0.52)	12.5
3	−2.32 (−3.00, −1.64)	11.4
4	−2.22 (−2.93, −1.52)	11.5
5	−1.39 (−2.18, −0.60)	12.4
6	−2.50 (−3.36, −1.63)	11.2
7	−2.76 (−3.50, −2.02)	11.0
8	−2.77 (−3.47, −2.06)	11.0
9	−4.44 (−5.18, −3.69)	9.3
10	−4.85 (−5.59, −4.11)	8.9

Note. CI = confidence interval. Analyses controlled for region of residence and for clustering by respondent.

Intention to be vaccinated against H1N1 (Table 3) was associated with older age, higher income, higher education, membership in a high-priority group for H1N1, and receipt of seasonal influenza vaccine the previous season. Intention to be vaccinated increased with perceived risk of contracting H1N1 and perceived risk of dying if infected. However, intention to be vaccinated decreased across progressive survey waves, with the largest decreases starting in September 2009 (when both perceived risk and observed disease activity were substantially increasing).

TABLE 3—

Results of Multivariate Linear Regression Models Predicting Intention to Be Vaccinated Against H1N1: American Life Panel Survey Respondents, 2009–2010

	Intention to Be Vaccinated (n = 17 464)
	b (95 CI)	Adjusted Mean (%)
Gender
Male	1.21 (−0.76, 3.18)	45.6
Female		43.6
Age, y	0.10 (0.03, 0.18)
25th percentile		43.2
75th percentile		45.4
Income, $
<25 000	Ref	39.1
25 000–49 999	2.12 (−1.09, 5.33)	44.6
50 000–74 999	2.26 (−1.04, 5.57)	43.7
>75 000	4.54 (1.34, 7.74)	46.8
Race
White	0.83 (−2.43, 4.09)	44.5
Non-White		43.4
Bachelor’s degree or higher	3.73 (1.60, 5.86)
Yes		47.9
No		41.8
High-priority group	3.78 (1.29, 6.28)
Yes		47.7
No		43.4
Receipt of seasonal influenza vaccine in prior y	37.18 (34.91, 39.45)
Yes		67.5
No		26.1
Perceived risk of contracting H1N1 in the next mo (per 1 change)	0.57 (0.52, 0.63)
25th percentile		38.5
75th percentile		46.5
Perceived risk of dying from H1N1 if infected (per 1 change)	0.13 (0.08, 0.18)
25th percentile		43.0
75th percentile		44.4
Survey wave
1	Ref	50.0
2	−0.90 (−1.98, 0.18)	49.0
3	−1.56 (−2.67, −0.46)	48.0
4	−3.39 (−4.57, −2.22)	46.3
5	−3.43 (−4.74, −2.12)	47.2
6	−3.31 (−4.84, −1.78)	48.0
7	−4.70 (−6.01, −3.40)	45.9
8	−12.90 (−14.41, −11.39)	41.7
9	−21.52 (−23.30, −19.76)	32.4
10	−14.00 (−15.90, −12.07)	36.4

Note. CI = confidence interval. Analyses controlled for region of residence and for clustering by respondent.

DISCUSSION

We took advantage of a unique opportunity to repeatedly survey a national sample of the US population at 10 points during the first year of the H1N1 influenza pandemic. To our knowledge, our study is the first to involve multiple surveys of this type over the course of the pandemic, drawing from a national panel of respondents.

Overall, the public’s perceived risk of contracting H1N1 in the month following each survey wave tracked objective markers of H1N1 influenza activity, both outpatient visits and hospitalizations. However, respondents grossly overestimated their risk of death from H1N1, with estimates ranging from about 10% to 14% depending on the time point. Perceived risk of death declined somewhat during the year, but estimates remained 100-fold higher than the 0.1% to 0.3% estimates cited in the President’s Council of Advisors on Science and Technology report released in August 2009.⁵ These data are in keeping with other studies of perceived disease risk, in which people tend to overestimate risk from rare events that are newsworthy and unusual.^23,24

Despite the exaggerated perception of risk of death, which did not decrease substantially across waves, intention to be vaccinated peaked at our first measurement in May 2009 and declined steadily, even in the face of growing numbers of H1N1 infections during the fall months. In fact, by the time that H1N1 vaccination became available in October and November 2009, many previously motivated members of the public were no longer interested in receiving it, a finding that helps to explain the suboptimal immunization rates achieved by the end of January 2010.

The fact that significant declines occurred even as the primary wave of the pandemic was building (although the timing of the pandemic varied by region) implies that people’s vaccination decisions were insensitive to the immediacy of the disease threat. Instead, our data are consistent with the idea that vaccination intentions may have been more directly related to the novelty of the risk²⁵ and declined as public health officials gained a more comprehensive understanding of the magnitude of the threat posed by the disease. Furthermore, even those who early on sought access to the vaccine were often unable to obtain it,¹ exacerbating a disconnection between vaccine supply and demand that probably had a negative impact on vaccine uptake.²⁶ These results further underscore the need for improved and timely vaccine supplies, because delays both allow disease to spread and appear to decrease people’s interest in taking steps to prevent additional spread.

Higher perceived risks of becoming infected with and dying from H1N1 were significantly associated with higher intentions to receive H1N1 vaccinations. In fact, a 1% increase in perceived risk of becoming infected with H1N1 corresponded to a 0.57% increase in intention to be vaccinated. Thus, those with a 10% higher perceived risk of becoming infected with H1N1 were 5.7% more likely to intend to be vaccinated against H1N1. A particularly intriguing finding was that lower income and education were significantly related to lower intention to be vaccinated for H1N1 but were simultaneously related to higher risk perceptions. This may suggest that these groups have particularly high distrust of novel vaccines. Alternately, these groups may simply be particularly poorly calibrated in their risk perceptions, perhaps because of lower health literacy and numeracy skills. Either way, it seems clear that addressing the needs of the less educated and less affluent is essential to optimize vaccine coverage.

Another strong predictor of H1N1 vaccination intentions was a history of being vaccinated against seasonal influenza in the prior season, even after control for age and membership in a high-priority group. This finding, which has been observed in previous studies of the H1N1 pandemic,^{11,12,27–31} highlights the need to vaccinate as many people as possible for seasonal influenza each year. Furthermore, only half of those patients who discussed H1N1 vaccination with a health care provider received a recommendation from the provider to obtain the vaccine,¹ a result mirrored in the low numbers of health care workers who were vaccinated. Therefore, efforts to inform both patient and provider decision-making are likely to yield considerable public health benefits beyond protection against seasonal influenza and are critical to preparedness for pandemic influenza.

However, the logistics of linking seasonal influenza vaccination to pandemic influenza vaccination are challenging. In this pandemic, for example, the priority groups for H1N1 vaccine were quite different from those for seasonal influenza vaccine in past years. In the future, this may represent less of a problem because the entire US population older than 6 months is now recommended to receive seasonal influenza vaccine annually.³²

Developing a targeted and effective public health communication strategy will depend on better understanding why those who have received seasonal influenza vaccine are more likely to intend to be vaccinated against H1N1. This subpopulation may be inherently more compliant with government vaccine recommendations or may have selectively benefited from more effective communication about influenza vaccine (whether seasonal or H1N1). They may have more accurate perceptions of the safety and effectiveness of influenza vaccine or a higher perceived need for the vaccine. In addition, it is well known that provider recommendations are a driving force in patient vaccination behavior,^33,34 and receipt of both seasonal and pandemic influenza vaccination is likely linked to frequency of patient–provider interactions. As a result, better education and increased acceptance of vaccinations by health care workers and providers could have positive secondary effects by increasing the likelihood of vaccination recommendations.

Limitations

The observational nature of our study limits our ability to comment definitively on causal relationships. However, the policy implications of our observations (e.g., need for more timely supply of vaccine, need for better education) do not depend on inferring causality. The study involved frequent assessments (10 surveys in 9 months) via a small set of questions, and we endeavored to use all available data. However, missing data were compounded across waves (a cost of administering multiple waves), which prevented repeated measures analyses of a core group of respondents in a regression analysis. Instead, we examined policy-relevant patterns of risk perceptions (e.g., their correspondence to changes in population infection rates) by focusing on repeated cross-sectional analyses, clustering by respondent for regression models when needed. Given that other studies have revealed that respondent self-reports of vaccination are reasonably reliable,^35,36 we relied on such self-reports. Obtaining objective verification of vaccination would be challenging on such a large scale.

No publicly available measure exists for actual risk of contracting H1N1 influenza at any given time. As a proxy for an objective measure of H1N1 activity, we used percentage of outpatient visits for influenza-like illness and hospitalizations, as reported by the CDC. Although these measures should accurately track actual H1N1 activity, the absolute numbers would underestimate the number of H1N1 infections in that not all infected people would seek medical care or require hospitalization. Thus, we were able to compare only patterns of perceived risk of contracting H1N1 with patterns of influenza activity; we cannot comment on whether our respondents overestimated or underestimated their individual risk. As well, one of our objective markers could have been influenced by perceived risk; thus, it might not be surprising that perceived risk of contracting H1N1 maps to proportion of visits for influenza-like illness. However, hospitalizations are unlikely to be influenced by risk perceptions.

The representativeness of our sample is underscored by the fact that the H1N1 vaccination rate among our respondents was very similar to the CDC national estimate (27% vs 24%). Using a consistent set of 3 core questions over time allowed us to examine longitudinal patterns and predictors of perceived risk of becoming infected with H1N1 influenza, perceived risk of death if infected, and intention to be vaccinated.

Conclusions

The public’s perception of risk of contracting H1N1 influenza tracked the actual evolution of the pandemic, but the risk of death from H1N1 influenza was overestimated even in light of objective data showing a relatively low risk of death. Despite such overestimates, intentions to receive H1N1 vaccination declined as the pandemic progressed, with decreases observed even as perceived risk (and disease activity) was increasing in September 2009. Those who perceived a higher risk of contracting and dying from H1N1 were more likely to intend to be vaccinated, but by far the strongest predictor of H1N1 vaccination intention was receipt of seasonal influenza vaccine in the previous year. Because prior seasonal influenza vaccination predicts future vaccination for H1N1, encouraging regular seasonal vaccination (both directly with patients and through support for provider recommendations) appears to be a valuable component of pandemic preparedness strategies.